YogaX builds AI-powered tools that handle customer chats, publish content on schedule, and keep sales operations running — so small teams can operate like much larger ones.
Three product lines, one goal: remove repetitive operational work with AI that is reliable enough to run unattended.
An AI assistant that lives inside Telegram and WhatsApp, answering product questions, taking orders, and escalating to a human only when it matters.
Scheduled publishing engine for social channels. Draft once, publish everywhere on a calendar — with engagement tracking per post.
Backend for social sellers: service catalog sync, balance management, order routing to fulfillment providers, and automated status updates.
How the products actually work — no magic, just careful engineering around large language models.
ChatOps is built on Claude's API for reasoning-heavy turns — order validation, complaint triage, upsell suggestions — with deterministic rule engines handling money movement. The LLM never touches balances directly; every financial action goes through an audited state machine.
PublishIQ treats content like a CI pipeline: drafts enter a queue, pass automated checks (format, length, media specs per platform), wait for their scheduled slot, then publish with retry logic. A background worker verifies each post actually went live.
SaleFlow abstracts multiple fulfillment providers behind one catalog. When a provider's API is slow or rejects an order, the system retries, reroutes, or refunds automatically — the buyer always gets a clear status, never silence.
Small businesses in Southeast Asia run on chat apps. Orders come through WhatsApp and Telegram at all hours, but owners can't be online 24/7 — so replies get delayed, orders get lost, and revenue leaks.
YogaX was founded in Jakarta in 2024 to fix exactly that: AI systems reliable enough that a two-person shop can offer round-the-clock service without hiring a night shift.
We're a small, engineering-led team. Every product we ship runs in production for real paying customers before we call it done — most of our roadmap comes directly from watching where our users' operations break.
We build on Claude's API for the reasoning layer because reliability matters more to us than novelty: when AI handles someone's money or customers, "mostly right" isn't good enough.
Tell us where your team loses time to repetitive work — we'll show you what automation actually looks like in production.
admin@yogax.my.id